2 hrs ago
AI-Generated Drug Shows Early Signs of Slowing Aging
Scientists are testing a medicine called rentosertib that was designed with help from artificial intelligence.
The medicine was tested in people who have a serious lung disease called IPF.
In the trial, 43 patients took the medicine for 12 weeks.
Six computer tools called aging clocks estimated that the patients’ bodies looked biologically younger afterward.
This does not prove that the patients will live longer or that the medicine truly slows aging.
The study was small, and the aging clocks may not always give reliable answers.
The medicine has not yet been tested in healthy people.
Experts say the results are encouraging but need to be confirmed in larger studies.
The drug also still needs further testing before it could receive regulatory approval.
Insilico Medicine’s drug candidate rentosertib reduced predicted biological age across six aging clocks in a 43-patient trial.
The trial involved patients with idiopathic pulmonary fibrosis, or IPF, a disease that scars lung tissue and limits oxygen flow.
Patients took rentosertib for 12 weeks, after which all six aging clocks showed lower predicted ages.
Researchers cautioned that the sample was small, aging clocks are not always reliable, and healthy patients were not tested.
Experts described the findings as promising but inconclusive, while noting that the drug remains years from possible regulatory approval.
- Who
- Insilico Medicine, led by founder Alex Zhavoronkov, conducted the trial involving 43 patients with idiopathic pulmonary fibrosis.
- What
- Researchers reported that AI-assisted drug candidate rentosertib reduced predicted biological age across six aging clocks.
- Where
- When
- Patients received the drug for 12 weeks; the new findings were published Monday in Nature Biotechnology.
- Why
- Rentosertib was developed to treat idiopathic pulmonary fibrosis, while the trial also explored whether it could affect markers associated with aging.
Evidence suggests promise
Experts urge caution
Biological-age results
Evidence suggests promise
All six aging clocks showed reduced predicted age after patients took rentosertib, and researchers described the finding as a clear reduction in predicted biological age.
Experts urge caution
Aging clocks are not always reliable, and lower predicted age does not yet establish that the drug slows aging or extends lifespan.
Strength of the evidence
Evidence suggests promise
The trial could provide a blueprint for future longevity studies and demonstrates how AI can support drug discovery and medical research.
Experts urge caution
The sample included only 43 patients with IPF, the drug has not been tested in healthy people, and experts say a definitive trial is still needed.
Readiness for use
Evidence suggests promise
Rentosertib previously showed potential to improve lung air capacity in patients with IPF.
Experts urge caution
The drug may still be years away from regulatory approval, even for treating patients with IPF.
Key facts
- Drug candidate
- Rentosertib
- Developer
- Insilico Medicine
- Disease studied
- Idiopathic pulmonary fibrosis, or IPF
- Trial participants
- 43 patients
- Treatment period
- 12 weeks
- Aging measures
- Six aging clocks
- Publication
- Nature Biotechnology
Quotes
Vadim Gladyshev
Harvard Medical School professor who helped build an aging clock
“This is the first study that shows, very clearly, that predicted biological age can be reduced.”
indianexpress.com
“But we do not yet have a definitive trial to make the final judgment.”
indianexpress.com
Evelyne Bischof
Tel Aviv University professor of medicine specializing in longevity
“These are methods we will use in future trials.”
indianexpress.com
Sources
Related news
Novo Nordisk Taps AWS as Preferred Cloud and AI Partner
AI Reshapes Patient-Centric Healthcare and Life Sciences Progress
Temple Acquires Longevous Ahead of Experimental Wearable Launch
Claude Produces Working Binders for 14 of 15 Drug Targets
Temple Acquires London Longevity Clinic Ahead of India Launch
UPSC GS-3 Practice Examines UPI Sustainability and AI Drug Discovery
